The Good, the Bad, and the Vision: Exploring the Mental Health Care Experiences of Transitional-Aged Youth Using the Photovoice Method
Bibliographic record
Abstract
Transitional-aged youth (TAY) between the ages of 16 and 24 experience higher rates of mental distress than any other age group. It has long been recognized that stability, consistency, and continuity in mental health care delivery are of paramount importance; however, the disjointed progression from paediatric to adult psychiatric services leaves many TAY vulnerable to deleterious health outcomes. In Spring 2019, eight TAY living with mental health challenges participated in a Photovoice study designed to: (1) illuminate their individual transition experiences; and, (2) support a collective vision for optimal mental health care at this nexus. Participants took photographs that reflected three weekly topics— the good, the bad, and the vision—and engaged in a series of three corresponding photo-elicitation focus group sessions. Twenty-four images with accompanying titles and captions were sorted into nine participant-selected themes. Findings contribute to an enhanced awareness of psychiatric service delivery gaps experienced by TAY, and advocate for seamless and supportive transitions that more effectively meet the mental health care needs of this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.081 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.042 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".